Method for providing access to online employment information

ABSTRACT

The present invention provides a method of managing employment data so as to provide access to the employment data via the Internet ( 18 ). The method including the steps of determining whether a web site ( 22, 24 ) contains employment data, formatting, parsing and storing the employment data and corresponding URL into a database, automatically searching the database ( 16 ) for matching employment data, and contacting the employer representative as to the matched employment data.

FIELD OF INVENTION

[0001] The present invention relates to employment services and, inparticular, to online recruiting or employment services.

BACKGROUND OF THE INVENTION

[0002] The rapid expansion of job postings on the Internet has created alarge amount of employment related information, which spans hundreds ofthousands of web sites. Initially, companies began posting their openjob positions on their own corporate web sites. A job seeker could thenreadily access new employment opportunities by visiting a company's website. As an increasing number of company web sites began to post theiropen jobs, however, the job search process grew proportionally. Forexample, a job seeker searching for a “software developer” positionwould have had to identify and visit the web site of every company thatmight have such open job positions. Thus, this growth resulted in a taskthat was cumbersome and time consuming for the job seeker.

[0003] In order to help address these issues, job board web sites haveevolved on the Internet. The original purpose of a job board was toprovide a single web site where companies could visit to post their openjob positions and job seekers could visit to search for new employmentopportunities. The job board concept helped the job seekers by creatinga central location that a job seeker could visit to search for jobs.

[0004] Unfortunately, however, the concept increased the work and costfor companies. In addition to maintaining job postings on their owncorporate web sites, companies were now required to visit the job boardsites to repost, update and delete their job position information asappropriate. The accuracy of the job board information was affected whencompanies changed their job information, filled open position, etc., butfailed to update the corresponding job board postings. These job boardsalso often charged a fee to the companies for this posting service. Inaddition, these job boards only contained job positions from companiesthat had actively posted jobs on the sites. In other words, companiesthat did not know about the job boards would have been prevented fromlisting the company's open positions and, consequently, eliminatedopportunities for the job seekers as well as the company itself.

[0005] Most recently, the aggregation, accuracy, and freshness of jobboard postings have been addressed through various web spidering orcrawling technologies. The technology of web site spidering or crawlingconsists of a process in which content from a set of source web sites isretrieved automatically. This content is typically retrieved for purposeof being indexed into a search engine web site in order to provideInternet users a central web site to use as a search tool. The type ofcontent that is spidered is generally not filtered so the search engineweb site often has indexed content from a wide variety of source websites. New web sites that contain content to be spidered have toregister with the search engine web site before their content isretrieved and indexed into the search engine. Once a new site isregistered into the set of source web sites to spider, the search engineweb site will periodically spider the site to search for new or updatedcontent to index.

[0006] In these updated models, the job board periodically sends outspiders to the web sites of companies that register with the job boardweb site. The purpose of these spiders is to retrieve and input thelatest job posting information from the company web sites and therebyautomatically update the job information listed on the job board. Themethod, however, creates a disadvantage for companies and job seekersbecause the sites do not post the numerous job positions from thecompanies that do not register with or know of the job board web site.As such, the Internet contains a vast amount of job postings which existonly on company job boards and which are not being collected anddisplayed by the job board web sites.

[0007] Another new approach to job posting aggregation is the mastersearch engine site. In this approach, the master web site collects a jobseelcer's search criteria and submits it to multiple other job board websites. The master search engine site aggregates the individual sites andpresents the results to the job seeker in a single format. An advantageto this method is that the job seeker only needs to visit a single siteto perform a job search. The disadvantages of this approach are that, asdescribed above, only a subset of the job board sites on the Internetare actually searched and individual company job postings are completelyomitted. Furthermore, in these types of searches, the formatting of theresults can vary thereby causing the job seeker to become confused whenpresented with search results.

[0008] An additional feature of prior art job board web sites is theelectronic notification of new job opportunities. When a new job isposted that fits within his selected category information, the jobseeker automatically receives notification of the new job via email. Alimitation to this system is that user may miss employment opportunitieswhich are filtered outside of the selected category information.

[0009] Another drawback of the prior art systems relate to the searchengines used for identifying a position of interest to the job seeker.The prior art systems use a table, key word or boolean driven searchengine. The search engines use a pull-down menu, keyword or booleansearch methodology that has a limited ability to implement intelligentsearches. For instance, a job seeker may be in search of a position in aspecific technical field. A search of job postings with one or twokeywords may identify many unrelated jobs. It may be very time consumingfor the job seeker to review every identified job posting. The effortbecomes even greater when compounded by the number of such searches tobe completed at each of the numerous online employment sites. The jobseeker may use additional keywords to reduce the number of unrelated jobpostings. However, the additional keywords often have the effect ofreducing certain of the job postings, which may be of interest to thejob seeker, but do not necessarily contain all of the designatedkeywords. In other words, the search strategy may have become toorestrictive. Therefore, the job seeker ends up accessing only a smallfraction of jobs currently available on the Internet.

[0010] Along with the evolution of job board related web sites, theprior art systems have provided job seekers the ability to postelectronically their resumes. These systems have increased the amount ofresumes available online. This increase has created web sites, whichcollect resumes into searchable databases. These web sites often sellsubscription access to their databases, which employers and recruiterspurchase in order to search for qualified candidates. However, these websites suffer from the same disadvantages and limitations as described inthe job posting process: a) companies and job seekers must visit the websites to add and update information; b) searches are limited to narrowlytargeted keywords; and c) job seeker resumes are sorted into restrictivecategories.

[0011] Furthermore, if these companies do not post at the job board websites, without adequate traffic to their corporate web site andemployment pages, employers cannot, on their own, reach a sufficientnumber of qualified candidates. As a result, the employers must chooseto either pay the third party job board web sites to post a portion oftheir jobs online, making these opportunities accessible to a largercandidate pool, or miss many qualified candidate. Despite thisinvestment, however, the factors listed above still limit theeffectiveness of the job boards and prevent many qualified candidatesfrom matching with the opportunities employers have paid to list.

[0012] In summary, there are deficiencies in the current state of theart in the Internet based employment process. The gap between job boardlistings and actual online jobs is growing rapidly. Companies developand add recruiting pages to their own web sites much faster than therate at which the top job boards add clients. Moreover, the gap betweenunique job board listings and unique jobs available online is expandingat an even faster pace, as companies that use job boards often post thesame opening to between six and ten sites. Furthermore, the current website job boards fail to aggregate completely all job postings on theInternet. Even the sites that aggregate a larger amount of the availablejob listings are limited by the search engine technology currently usedby those job boards. In addition, the current prior art systems aredeficient in their information exchange capabilities. Job board websites rely on companies and/or job seekers to continually visit the jobboard web sites and update the applicable information.

SUMMARY OF THE INVENTION

[0013] The object of the present invention is a method of managingemployment data to provide enhanced access via the Internet to theemployment data.

[0014] A further object of the present invention is to provide a morethorough and precise searching of the employment data.

[0015] Still a further object of the present invention is to updateautomatically the employment data collected by the present invention.

[0016] Still yet a further object of the present invention is to formatthe employment data so as to allow for a more accurate and efficientsearch of the employment data.

[0017] Still yet a further object of the present invention is to matchautomatically users to fulfill employment needs.

[0018] In general, the present invention consists of several keysubsystems. These subsystems are based on existing software technology,information spidering and concept based searching, which is new in itsapplication to the Internet related employment industry.

[0019] The present invention builds on the technology of job spideringand aggregation and incorporates it into the employment field. Forexample, the working set of web sites which this system spiders includesthe entire Internet directory (“Dot Com database”). Thus, both companiesand job boards are included in the job posting collection. Furthermore,the use of spidering technology is extended to resume collection as wellas spidering of job postings. This allows the creation of a much morecomprehensive and complete database of the available employment data.

[0020] The present invention also applies a concept based search engineto the employment search and match problem. As noted above, prior artsearch engine web sites are commonly based on keyword search enginetechnology. In its simplest form, a keyword search takes a set of commadelimited user input words and scans its document set for one or moreword or partial word matches. Keyword searches, however, have beenenhanced to include word count statistics, i.e., how often a wordappears in a document increases its relevancy, and boolean operators,i.e., a user can search for specific terms to return documents that mustcontain both words. Unfortunately, these searches remain as simple wordpattern matching technology, and the casual Internet user does notnecessarily possess a clear understanding of query word relevancy orboolean logic.

[0021] In order to improve the user search experience, concept basedsearch engines were created. The premise of a concept based searchengine is that it is able to “learn” thematic information regarding thedocuments that it indexes. This learning is typically accomplished byapplying Bayesian reasoning and neural network technology to eachdocument when it is indexed. Users are often able to search the databaseby using full sentence, natural language queries instead of keyword setsand boolean logic. As a concept based search engine learns its documentset, it can also make distinctions and relations. This learnedinformation allows a user to search effectively for information withoutknowing exactly what is being sought or how the query should be phrased.

[0022] Another important feature of a concept based search engine isthat the user will always be provided with some form of results. Theresults from such a search engine are typically returned in descendingweight order. A result with 100% weight is highly relevant to the user'squery, while a result with 1% weight contains little or no relevance tothe search. This behavior is a key feature of the concept based searchengine, because it allows a programmatic decision to be made based onthe “goodness” of a particular result.

[0023] The use of a concept based search engine in the present inventioneliminates the need for the user to categorize a job posting or resumeinto a fixed category list and to rely on simple keyword based searchesto find information, thereby providing an accurate and thorough searchresult. The present invention then automatically spiders job and resumerelated web sites for content, indexes the content into its conceptbased search engines, matches the content between jobs and resumes, andnotifies companies and job seekers of new mutual opportunities. Thisprocess occurs continuously to maximize the timeliness and freshness ofthe information exchange.

[0024] Also, the present invention is able to accept a wide range of jobposting formats and resume formats. The format of a job posting orresume will vary, often significantly, from web site to web site and jobseeker to job seeker. By enhancing the process with newly developedsoftware, which targets the online employment information, the system isable to index this diverse data into a common format. Once in a commonformat, matches within the data between job postings and resumes areefficiently performed.

BRIEF DESCRIPTION OF THE DRAWINGS

[0025]FIG. 1 is a functional block diagram of the system of the presentinvention.

[0026]FIG. 2 shows a functional flowchart for creating and accessing adatabase of employment data available on the Internet.

[0027]FIG. 3 shows a flow chart for determining if the visited web sitesmeet the employment criteria.

[0028]FIG. 4 shows a flow chart for updating automatically theemployment data stored in the database.

[0029]FIG. 5 shows a flow chart for formatting and parsing theemployment data.

[0030]FIG. 6 shows a flow chart for adjusting the revisitation period ofthe visited web sites.

[0031]FIG. 7 shows a flowchart showing the aging and deletion step.

[0032]FIG. 8 shows a flow chart for collecting subscriber searchcriteria and conducting a concept-based search using the criteria.

[0033]FIG. 9 shows a flowchart of matching the employment data andnotifying the users.

[0034]FIG. 10 provides a table depicting employment data.

DETAILED DESCRIPTION OF THE INVENTION

[0035] With reference to FIG. 1, a system 10 of managing employment datais shown. The system 10 includes a dedicated spidering server 12, adedicated search, retrieve and process server 14 and a database 16. Thesystem 10 provides users (not shown) with the ability to search, via theInternet 18, for employment data located at public job boards 20,corporate web sites 22 and other web sites 24. Users are provided accessto the system 10 via user Internet connections 26. The Internetconnections 26 may be personal computers, for example.

[0036] The dedicated spidering server 12 is used to search the Internetfor the employment data. FIG. 10 provides a table showing an example ofemployment data 28 or information available via the Internet 18. Oncethe employment data is located, relevant information is loaded into thedatabase 16. The dedicated search, retrieve and process server 14provides the user the ability to search the database 16 for employmentdata. Users include corporation representatives seeking to fill aposition, agents working for the corporations, as well as individualsseeking an employment position. The process server 14 also conductsautomatic searches of the database for matching employment data (i.e.,matching jobs and resumes).

[0037] It will become clear from FIG. 2 that the database 16 of FIG. 1represents multiple databases having individual functions. FIG. 2discloses a process or functional block diagram of the presentinvention. In particular, FIG. 2 discloses a process which dynamicallyretrieves and indexes large amounts of web employment data and processesthis information in an efficient and timely manner. The Dot Corndatabase 30 contains a listing of all the active domain names on theInternet 18. The prequalify dictionary 32 consists of a concept basedsearch engine that has been loaded with template documents to identifyweb pages that contain job posting or resume information. The siteprequalification step 34 receives input from the Dot Corn database 30and the prequalify dictionary 32. The site prequalification step 34filters web sites that contain job postings or resumes. The output ofstep 34 includes URL records, which are stored in the active spider'sdatabase 36. Step 34 is shown in greater detail in FIG. 3. Step 3.2 ofFIG. 3 begins with reading the prequalify dictionary 32. Step 3.3 readsthe next record from the Dot Corn data base 30. Step 3.5 consists ofdetermining whether the record is scheduled for a check. At step 3.6,each record is checked against the Internet domain named service (DNS)to verify whether an active web site exists for the domain name. In theevent it is determined that an active web site does not exist, then step3.13 consists of scheduling the web site or record for a future check.In the event the web site is active, step 3.8 consists of fetching thecontent of the web site. Step 3.10 consists of checking the site contentagainst the prequalify dictionary 32. The prequalify dictionary 32contains a concept base search engine which has been configured withtemplate sample documents of job postings and resumes. Each page of sitecontent that is retrieved at step 3.8 is presented as a query input tothe prequalify dictionary concept based search engine at step 3.10. Thesearch engine returns a rated percent result, which indicates howrelevant a particular site page is with respect to job postings orresumes. If a web site is determined to contain documents of sufficientrelevancy, the site is stored in the active spider's database 36,enabling the site to be regularly spidered for its content. The retrievecontent is stored in the spidered content database 38. If a web sitedoes not exist or has no relevant content, it is scheduled at step 3.13for a future check, at which time the site prequalification step 34 willrevisit the site to repeat the foregoing process.

[0038] The site prequalification step 34 contains several key operatingparameters, including the maximum number of pages to retrieve from asingle web site, the amount of time to spend spidering a single web siteand a threshold relevancy wait that is used to indicate whether the sitecontains job postings or resumes of related content. Critical to thisstep is the configuration of the prequalify dictionary 32, as itsdocument set is the mechanism that controls which web sites are acceptedas valid and which are rejected. The architecture of a site groupprequalification step 34 is readily scalable, as in practice severalservices can be operating in parallel on the Dot Corn data base 30 toperform the web site validation process. By scaling services in thismanner, the information scan rate of the millions of records of the DotCorn database 30 is easily controlled.

[0039] The periodic spidering step 40 of FIG. 2 is responsible forrunning each of the spiders in the active spider's database 36 on aregular, scheduled basis. FIG. 4 discloses the periodic spidering step40 in greater detail. Step 4.2 consists of reading the next record fromthe active spider's database 36. Step 4.4 determines whether the website corresponding to the record is scheduled to be spidered. In theevent the web site is scheduled to be spidered, step 4.5 fetches thesite content. Step 4.7 determines whether the newly fetched content haschanged from the corresponding content previously stored in the spideredcontent database 38 (FIG. 2) to determine whether the web site haschanged. If a change has occurred, the new content is stored in thespider content database 38 for further processing.

[0040] If it is determined at step 4.6 that the spider fails whenaccessing a particular web site, step 4.9 consists of identifying thesite as “failed” and removing the sit& from the active spider's database36. Step 4.10 updates the Dot Corn database 30 to schedule the site tobe requalified at a later time.

[0041] Step 40 is designed to run continuously to ensure that when thecontent of each source site changes, it is quickly updated in the spidercontent database 38. Thus, the timeliness and freshness of theinformation is preserved. Step 40 is readily scalable, as in practiceseveral services can be operated and parallel to perform this spideringprocess. As additional spiders are created, additional service can beadded to handle the new load.

[0042] The content processing step 42 of FIG. 2 consists of furtherprocessing the content, which is temporarily stored in the spidercontent database 38. The processing dictionary 44 consists of a conceptbased search engine, which is similar to the prequalify dictionary 32.The search engine has been loaded with additional template documentsthat enable spidered content to be parsed and scrubbed prior to beingloaded into the searchable content database 46. The content processingstep 42 is shown in greater detail in FIG. 5. The content processingstep 42 is responsible for processing each retrieved document into aformat that is suitable for indexing into the searchable contentdatabase 36. The processing dictionary 44 contains a concept basedsearch engine, which has been configured with documents that containspecific job titles, job descriptions and resume descriptions. Thedictionary 44 is used to measure the relevance of each spidered contentdocument to determine whether it should be classified as a job-posting,resume or irrelevant, at which time the content is discarded. Anothertask of step 42 is the parsing and analysis of web pages, which containmultiple sets of information. For example, a single web page, whichcontains 15 different job postings, is broken down into 15 separatedocuments utilizing available advanced document parsing technology. Eachdocument would contain its own title and specific job locationinformation. The improved content results in a search experience that isclear and concise to the user.

[0043] Step 5.2 consists of reading the processing dictionary 44. Step5.3 consists of reading the next record from the spidered content database 38. Step 5.5 strips the document of its hypertext markup language(HTML) commands. The stripped document is evaluated by step 5.6 for itslength requirements, and is scanned at step 5.7 and 5.8 to identify thelocation information (city, state, and zip code), and the e-mail addressinformation.

[0044] The document is then presented as query input through theprocessing dictionary 44. The concept based search engine is used tofurther identify the document as a job posting or resume as well asdetermine its title information and amount of different informationwhich the document may contain (see step 5.9). Documents that do notmeet minimum relevancy requirements as a job posting or resume arediscarded (step 5.10 and 5.12). Documents that pass the noted criteriaare indexed into the searchable content database 46 as a job posting orresume (step 5.13).

[0045] After a document passes through this process, its record in thesearchable content database 46 represents a uniform entry, which isconsistent with the other records. The content processing step 42 isdesigned to run continuously as new information is placed into thespidered content database 38. Thus, the timeliness and freshness of theinformation is preserved. Step 42 is readily scalable, as in practiceseveral servers can be operating in parallel to perform the contentprocessing. As the input spidering process information flow increases,additional servers can be added to handle the new content processingload.

[0046] The spider adaptation step 48 of FIG. 2 is responsible fordynamically adjusting the operating parameters of each spider. Theadaptation step 48 is shown in greater detail in FIG. 6. Step 6.2consists of reading the next site of which the content was previouslyprocessed and stored in the searchable content database 46. In the eventit is determined at step 6.4 that the particular spider failed orretrieved irrelevant content (not job posting or resume relatedcontent), then step 6.10 sets the spider status as “failed” in theactive spider data base 36, and at step 6.11, the Dot Corn data base 30is updated to requalify the failed site at a later time.

[0047] Step 6.5 compares the content retrieved at step 6.2 with thecontent previously stored in the searchable content database 46. Step6.6 determines whether the changed limit has been exceeded. Based on theamount of changes that have occurred, the spider schedule will beadjusted accordingly. In the event the change limit has been exceeded,then step 6.12 will set the spider to run again the following day. Inthe event the change limit has not exceeded, then step 6.7 and 6.8 willincrease the spider frequency for that particular site by an additionalday if the delay is presently less than 30 days. The spider adaptationstep 48 is designed to run continuously as a feedback loop between thecontent processing step 42 and the periodic spidering step 40. Step 48is readily scalable, as in practice several servers can be operating inparallel to perform this step 48. As the input spidering processinformation flow increases, additional service can be added to handlethe new load.

[0048] The aging and deletion step 50 is responsible for expiring oldinformation in the searchable content database 46. The aging anddeletion step 50 is shown in greater detail in FIG. 7. Step 7.2 readsthe next record from the searchable content data base 46. Step 7.4determines whether the document date has expired. In the event thedocument date has expired, step 7.5 deletes the document from thesearchable content database 46. Step 50 ensures that old web sites thathave been removed from the Internet are identified, and their contentdocument sets are purged from the overall system. The aging and deletionstep 50 is designed to run continuously, and it is readily scalable, asin practice several servers can be operating in parallel to perform thisaging and deletion step. As the input spidering process information flowincreases, additional servers can be added to handle the new load.

[0049] The result of the foregoing provides a searchable contentdatabase 46 of job positions and resumes, which may be “manually”searched by users as well as searched via an automatic process.

[0050] The “manual” search is initiated at the user search step 52 andcontinues with the concept phase step 54, the keyword phase step 56 andconcludes with the search results 58. FIG. 8 discloses additionaldetails as to the user search. Step 8.2 consists of reading the usersearch input. Step 8.3 determines whether the title, description or keywords have been entered. However, the user may further includeinformation such as the city, state, range of location and number ofresults returned, etc. The concept phase step 54 occurs at step 8.6whereupon concept searching is conducted upon the searchable contentdatabase 46 using the user input. The results are processed at step 8.8whereupon traditional text processes and techniques are used on theresult to produce a filtered result set. Step 8.9 determines whether thequantity of the results meets the users specified quantity in order todetermine whether the search may be concluded.

[0051] The user search step provides a front-end, manual interface forjob seekers and employers or recruiters to search for employment data,i.e., job postings or resumes, respectively. The job seeker's search isprovided as a free service, whereas the resume search is sold as asubscription service.

[0052] The user search is designed to run on user demand, and is readilyscalable, as in practice several servers can be operating in parallel toservice multiple user search requests. As the number of new userssearching the system increases, additional servers can be added tohandle the new load.

[0053] The automatic match step 60 is responsible for identifyingmatches between the employer's (job postings) and job seekers (resumes).As matches are identified, both the employer and job seeker are notifiedvia e-mail. FIG. 9 discloses the automatic match step 60 in greaterdetail.

[0054] Step 9.2 consists of reading the next new job posting from thesearchable content database 46. Step 9.4 consists of using the contentsof the new job posting as query input to perform a concept based searchon the resumes in the searchable content data base 46. The results ofthis search consist of a set of resumes that meet a relevant percentrate with respect to the job posting content. The candidates of theseresumes are identified as “good matches” for a particular job posting.At steps 9.6 and 9.7, the employer corresponding to the new job postingand the candidates corresponding to the identified resumes, arecontacted via e-mail.

[0055] Step 9.8 consists of reading the next new resume from thesearchable content data base 46. At step 9.10, the contents of the newresume are used as query input to perform a concept based search on thejob postings in the searchable content database 46. The results of thissearch consist of a set of job postings that meet a relevant percentrate with respect to the resume content. The jobs are identified as“good matches” for the particular candidate. Steps 9.12 and 9.13 consistof contacting the employers corresponding to the job posting results,and the candidate corresponding to the new resume.

[0056] When a candidate receives an e-mail message containing the jobdescription(s), the candidate is able to access the job posting details,company information, etc. free of charge. Once the candidate reviewsthis information, the candidate may choose to apply to a job, also freeof charge. When an employer or recruiter receives the e-mail messageidentifying an eligible candidate(s) and the qualification summaries,the employer or recruiter may elect to purchase a web site subscription,which allows access to each candidate's resume and contact information.Furthermore, when an employer or recruiter subscribes to the web siteand accesses various candidate information, the employer or recruitermay also elect to engage recruiting services to assist in pursuing thecandidate.

[0057] The automatic match step 60 is designed to run continuously asnew job postings and resumes are added to the searchable contentdatabase 46. The match step 60 is scalable, as in practice severalservers can be operated in parallel to perform this matching and e-mailnotification process. As the input information flow to the searchablecontent database 46 increases, additional servers can be added to handlethe new load.

1. A method of managing employment data so as to provide access to theemployment data via the Internet, the method comprising the steps of:collecting the employment data from the information available on theInternet; formatting, parsing and storing the employment data andcorresponding URL into a database; automatically updating the employmentdata stored in the database; matching the employment data; and providinga representative of a non-subscribing entity looking to fill a jobposition the employment data from the matching step, whereby employmentneeds are fulfilled.
 2. The method of claim 1, wherein employment dataincludes job openings, job postings, job listings, resumes and relatedemployment information.
 3. The method of claim 1, wherein the step ofproviding includes a non-solicited contacting of the representative. 4.The method of claim 3, wherein the step of contacting the representativeis via email.
 5. The method of claim 1, further comprising makingavailable a placement service.
 6. The method of claim 1, furthercomprising revisiting the websites that meet the employment datacriteria on a periodic basis to determine whether the content haschanged.
 7. The method of claim 6, further comprising expanding theperiodic revisiting time if the content has not changed.
 8. A method ofmanaging employment data so as to provide access to the employment datavia the Internet, the method comprising the steps of: collecting theemployment data from the information available on the Internet;formatting, parsing and storing the employment data and correspondingURL into a database; automatically updating the employment data storedin the database; matching employment data; and making availableplacement services, whereby employment needs are fulfilled.
 9. A methodof providing access to employment data via the Internet, the methodcomprising the steps of: establishing valid employment data criteria;randomly visiting web sites on the Internet; examining the visitedwebsites; determining if the visited websites meet the employment datacriteria; storing the URL corresponding to the visited websites thatmeet the employment data criteria and information relevant to thecontent of the visited websites into a database; and providing access toemployment data via the database, whereby employment needs can befulfilled.
 10. The method of claim 9, further comprising revisiting thewebsites that meet the employment data criteria on a periodic basis todetermine whether the content has changed.
 11. The method of claim 10,further comprising expanding the periodic revisiting time if the contenthas not changed.
 12. The method of claim 9, further comprisingrevisiting the websites that meet the employment data criteria on aperiodic basis to determine whether the websites still meet theemployment data criteria.
 13. The method of claim 12, further comprisingremoving the URL and the corresponding content from the data base afterdetermining the website no longer meets the employment data criteria.14. The method of claim 9, wherein the step of determining if thevisited websites meet the employment criteria is done through conceptsearching.
 15. The method of claim 14, wherein the step of concept-basedsearching includes using concept-based software.
 16. A method ofproviding access to employment data via the Internet, the methodcomprising the steps of: creating a database of employment data;establishing employment needs criteria; and searching the database basedon the criteria and using concept searching, whereby more accurate andcomprehensive data is returned.
 17. The method of claim 16, wherein thestep of concept-based searching includes using concept-based software.18. A method of managing employment data so as to provide access to theemployment data via the Internet, the method comprising the steps of:collecting the employment data from the Internet; formatting, parsingand storing the employment data into a database; and providing access toemployment data in a common format via the database, whereby employmentneeds are fulfilled.
 19. The method of claim 18, wherein the formattingand parsing the employment data is done by using formatting software.20. A method of providing access to employment data via the Internet,the method comprising the steps of: searching the Internet foremployment data posted on the Internet; determining a URL for theemployment data identified in the searching step; and maintaining anindex database for the employment data identified in the searching step,the index database including the respective URL for the employment dataidentified in the searching step, whereby once the database is formed,it can be searched by a user.
 21. The method of claim 20, furthercomprising the steps of determining the keywords for the employment dataidentified in the searching step, and maintaining the index database toinclude the respective URL and the keywords for the employment dataidentified in searching step.
 22. The method of claim 21, furthercomprising the steps of routinely revisiting the URL to determine ifinformation, regarding the employment data posted at the URL, haschanged, and automatically updating the index database with any changedinformation.
 23. The method of claim 20, further comprising the step of:continuously searching the Internet for new information regardingemployment data posted on the Internet; and updating the index databasewith the new information.
 24. The method of claim 20, wherein the stepof searching the Internet includes searching the Internet for employmentdata using concept searching.
 25. The method of claim 24, wherein thestep of concept-based searching includes using concept-based searchsoftware.
 26. A method of managing employment data so as to provideaccess to the employment data via the Internet, the method comprisingthe steps of: determining whether a web site contains employment data;formatting, parsing and storing the employment data and correspondingURL into a database; automatically searching the database for matchingemployment data; and contacting the employer representative as to thematched employment data.
 27. The method of claim 26, wherein the step ofcontacting includes providing the employer representative with a portionof the matching employment data and offering all of the matchingemployment data upon the purchase of a subscription.
 28. The method ofclaim 26, further comprising providing the employer representative theauthority to search the database for matching employment data, providinga portion of the matching employment data and offering all of employmentdata upon the purchase of a subscription.
 29. The method of claim 26,further comprising the steps of confirming that a previously visited website continues to contain employment data, and removing the previouslystored employment data and corresponding URL from the database in theevent the revisited web site no longer contains employment related data.30. The method of claim 26, further comprising the steps of revisitingand determining whether a previously visited web site has revisedemployment data, and formatting parsing and storing the revisedemployment data and respective URL into the database for each web sitewhich has revised the employment data.
 31. The method of claim 30,further comprising the step of adjusting the period of revisiting basedon the degree to which the employment date has been revised.